9 resultados para Shared component model


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Situation Background Assessment and Recommendation (SBAR): Undergraduate Perspectives C Morgan, L Adams, J Murray, R Dunlop, IK Walsh. Ian K Walsh, Centre for Medical Education, Queen’s University Belfast, Mulhouse Building, Royal Victoria Hospital, Grosvenor Road, Belfast BT12 6DP Background and Purpose: Structured communication tools are used to improve team communication quality.1,2 The Situation Background Assessment and Recommendation (SBAR) tool is widely adopted within patient safety.3 SBAR effectiveness is reportedly equivocal, suggesting use is not sustained beyond initial training.4-6 Understanding perspectives of those using SBAR may further improve clinical communication. We investigated senior medical undergraduate perspectives on SBAR, particularly when communicating with senior colleagues. Methodology: Mixed methods data collection was used. A previously piloted questionnaire with 12 five point Lickert scale questions and 3 open questions was given to all final year medical students. A subgroup also participated in 10 focus groups, deploying strictly structured audio-recorded questions. Selection was by convenience sampling, data gathered by open text questions and comments transcribed verbatim. In-vivo coding (iterative, towards data saturation) preceded thematic analysis. Results: 233 of 255 students (91%) completed the survey. 1. There were clearly contradictory viewpoints on SBAR usage. A recurrent theme was a desire for formal feedback and a relative lack of practice/experience with SBAR. 2. Students reported SBAR as having variable interpretation between individuals; limiting use as a shared mental model. 3. Brief training sessions are insufficient to embed the tool. 4. Most students reported SBAR helping effective communication, especially by providing structure in stressful situations. 5. Only 18.5% of students felt an alternative resource might be needed. Sub analysis of the themes highlighted: A. Lack of clarity regarding what information to include and information placement within the acronym, B. Senior colleague negative response to SBAR C. Lack of conciseness with the tool. Discussion and Conclusions: Despite a wide range of contradictory interpretation of SBAR utility, most students wish to retain the resource. More practice opportunities/feedback may enhance user confidence and understanding. References: (1) Leonard M, Graham S, Bonacum D. The human factor: the critical importance of effective teamwork and communication in providing safe care. Quality & Safety in Health Care 2004 Oct;13(Suppl 1):85-90. (2) d'Agincourt-Canning LG, Kissoon N, Singal M, Pitfield AF. Culture, communication and safety: lessons from the airline industry. Indian J Pediatr 2011 Jun;78(6):703-708. (3) Dunsford J. Structured communication: improving patient safety with SBAR. Nurs Womens Health 2009 Oct;13(5):384-390. (4) Compton J, Copeland K, Flanders S, Cassity C, Spetman M, Xiao Y, et al. Implementing SBAR across a large multihospital health system. Jt Comm J Qual Patient Saf 2012 Jun;38(6):261-268. (5) Ludikhuize J, de Jonge E, Goossens A. Measuring adherence among nurses one year after training in applying the Modified Early Warning Score and Situation-Background-Assessment-Recommendation instruments. Resuscitation 2011 Nov;82(11):1428-1433. (6) Cunningham NJ, Weiland TJ, van Dijk J, Paddle P, Shilkofski N, Cunningham NY. Telephone referrals by junior doctors: a randomised controlled trial assessing the impact of SBAR in a simulated setting. Postgrad Med J 2012 Nov;88(1045):619-626.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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During the years of political violence in Northern Ireland many looked to schools to contribute to reconciliation. A variety of interventions were attempted throughout those years, but there was little evidence that any had produced systemic change. The peace process provided an opportunity for renewed efforts. This paper outlines the experience of a series of projects on 'shared education', or the establishment of collaborative networks of Protestant, Catholic and integrated schools in which teachers and pupils moved between schools to take classes and share experiences. The paper outlines the genesis of the idea and the research which helped inform the shape of the shared education project. The paper also outlines the corpus of research which has examined various aspects of shared education practice and lays out the emergent model which is helping to inform current government practice in Northern Ireland, and is being adopted in other jurisdictions. The paper concludes by looking at the prospects for real transformation of education in Northern Ireland.

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The potential for serum amyloid P-component (SAP) to prevent cardiac remodeling and identify worsening diastolic dysfunction (DD) was investigated. The anti-fibrotic potential of SAP was tested in an animal model of hypertensive heart disease (spontaneously hypertensive rats treated with SAP [SHR - SAP] × 12 weeks). Biomarker analysis included a prospective study of 60 patients with asymptomatic progressive DD. Compared with vehicle-treated Wistar-Kyoto rats (WKY-V), the vehicle-treated SHRs (SHR-V) exhibited significant increases in left ventricular mass, perivascular collagen, cardiomyocyte size, and macrophage infiltration. SAP administration was associated with significantly lower left ventricular mass (p < 0.01), perivascular collagen (p < 0.01), and cardiomyocyte size (p < 0.01). Macrophage infiltration was significantly attenuated in the SHR-SAP group. Biomarker analysis showed significant decreases in SAP concentration over time in patients with progressive DD (p < 0.05). Our results indicate that SAP prevents cardiac remodeling by inhibiting recruitment of pro-fibrotic macrophages and that depleted SAP levels identify patients with advancing DD suggesting a role for SAP therapy.

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Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

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Legionella pneumophila, the causative agent of a severe pneumonia named Legionnaires' disease, is an important human pathogen that infects and replicates within alveolar macrophages. Its virulence depends on the Dot/Icm type IV secretion system (T4SS), which is essential to establish a replication permissive vacuole known as the Legionella containing vacuole (LCV). L. pneumophila infection can be modeled in mice however most mouse strains are not permissive, leading to the search for novel infection models. We have recently shown that the larvae of the wax moth Galleria mellonella are suitable for investigation of L. pneumophila infection. G. mellonella is increasingly used as an infection model for human pathogens and a good correlation exists between virulence of several bacterial species in the insect and in mammalian models. A key component of the larvae's immune defenses are hemocytes, professional phagocytes, which take up and destroy invaders. L. pneumophila is able to infect, form a LCV and replicate within these cells. Here we demonstrate protocols for analyzing L. pneumophila virulence in the G. mellonella model, including how to grow infectious L. pneumophila, pretreat the larvae with inhibitors, infect the larvae and how to extract infected cells for quantification and immunofluorescence microscopy. We also describe how to quantify bacterial replication and fitness in competition assays. These approaches allow for the rapid screening of mutants to determine factors important in L. pneumophila virulence, describing a new tool to aid our understanding of this complex pathogen.

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This article considers how the education systems of divided societies have been shaped in response to the experience of ethnic and religious conflict. The analysis identifies two competing priorities in such contexts – the development of social cohesion and the protection of cultural, ethnic and religious identities - and explores how these may be reconciled through a model of ‘shared education’. Drawing on research evidence and recent experience of shared education in relation to Northern Ireland, the Former Yugoslav Republic of Macedonia and Cyprus, we reflect on the advantages and challenges of this model in areas experiencing conflict and division.

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This paper argues that an important part of ensuring the jurisdictional basis of the crime of aggression is to secure a partnership between the UN Security Council and the ICC. Such a partnership should be conducive towards the reality of holding to account individuals that undertake an illegal use of force. This Paper puts forward guiding principles for a model that would benefit a constructive institutional relationship between the Council and the Court. It is through the application of these five guiding principles that the inclusion of the crime of aggression in the Rome Statute can translate into a constructive relationship between the International Criminal Court and the Security Council for the betterment of international peace and security as well as international justice. I maintain that it would be damaging to both the legitimacy and operational effectiveness of the Security Council and the ICC and detrimental to the overall institutional relationship if the final outcome proves unfavourable to international action against the crime of aggression and nothing more than dead letter law. Essentially the key to a viable cooperation regime between the Court and the Council will hinge on shared objectives regarding the crime of aggression rather than opposing views, namely combating impunity by holding individuals accountable for the illegal use of force.